Luan Vardari - Böcker

Crime, finance, and the law have always been in delicate balance; in the internet era, there becomes a growing need for modern techniques to combat financial misconduct. In Corruption and Crime in Finance: Legal and Economic Perspectives, key offenses such as corporate fraud, money laundering, and insider trading are analysed, highlighting how greed, inequality, and competitive pressures foster corruption – and how legal frameworks can deter such offenses.Using real-world case studies, chapters expose vulnerabilities in financial systems and regulatory oversight, offering insights into notorious instances of corporate misconduct. Diving into global legal frameworks and the role of organisations such as the Financial Action Task Force (FATF) in fighting back against cybercrime, crypto fraud, and protecting digital finance globally, Corruption and Crime in Finance considers the sociopolitical and developmental impacts of financial crime. It shows how corruption and fraud perpetuate economic inequality, restrict access to essential resources, and inhibit economic growth, particularly in emerging markets.Advocating for transparency and whistleblowing as essential tools in exposing and preventing financial crime and suitable for scholars, policymakers, legal professionals, and finance industry experts, Corruption and Crime in Finance provides actionable next steps to foster a more just global financial system, seamlessly blending theory and reality.

The operations of the banking and finance sectors have greatly changed as they have integrated new and innovative smart technologies. Evolving digital technologies such as machine learning and artificial intelligence have given business and financial analysis new tools that provide the opportunity to analyze financial information for better decision making and market risk management. This new volume looks at these developments through a definitive assessment of how AI and ML have influenced today’s business finance processes. It explores the opportunities and risks that may originate from fintech as well as the ethical issues connected with artificial intelligence and machine learning. It looks at the changing landscape of investments, the confluence of social commerce and machine learning, assessing customer awareness and engagement in green banking, machine learning algorithms for forecasting, gender bias in investment behavior through machine learning, and much more.